• 한국운동역학회지
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• 제17권2호
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• pp.177-185
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• 2007

Even though there were no clear definitions of the short game and short game distance, short game capability is crucial for a good golf score. Generally, chip shot and pitch shot are regarded as two principal components of the short game. Chip shot is a short, low trajectory shot played to the green or from trouble back into play. Pitch shot is a high trajectory shot of short length. Biomechanical studies were conducted usually to analyze full swing and putting motions. The purpose of the study was to reveal the kinematical differences between professional golfers' 30 yard $53^{\circ}wedge$ chip shot and $56^{\circ}wedge$ pitch shot motions. Fifteen male professional golfers were recruited for the study. Kinematical data were collected by the 60 Hz three-dimensional motion analysis system. Statistical comparisons were made by paired t-test, ANOVA, and Duncan of the SPSS 12.0K with the $\alpha$ value of .05. Results show that both the left hand and the ball were placed left of the center of the left and right foot at address. The left hand position of the chip shot was significantly left side of that of the pitch shot. But the ball position of the pitch shot was significantly right side of that of the chip shot. All body segments aligned to the left of the target line, open, at address. Except shoulder, there were no significant pelvis, knee, and feet alignment differences between chip shot and pitch shot. These differences at address seem for the ball height control. Pitch shot swing motions(the shoulder and pelvis rotation and the club head travel distance) were significantly bigger than those of the chip shot. Club head velocity of the pitch shot was significantly faster than that of the chip shot at the moment of impact. This was for the same shot length control with different lofted clubs. Swing motion differences seem mainly caused by the same shot length control with different ball height control.

• 한국지능시스템학회논문지
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• 제11권6호
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• pp.465-469
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• 2001

In injection molding short shot is one of the frequent and fatal defects. Experts of Injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is most economic way in time and cost. However, it is difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a modular fuzzy neural network (MFNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mo이 temperature is recommenced by the NFNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part. and appropriate mold temperature is recommend repeatedly through the NFNN.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.83-86
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• 2001

In injection molding, short shot is one of the frequent and fatal defects. Experts of injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is the most economic way in time and cost. However it is a difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a fuzzy neural network(FNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mold temperature is recommended by the FNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part, an appropriate mold temperature is recommend repeatedly through the FNN.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.402-405
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• 2001

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• 마이크로전자및패키징학회지
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• 제8권4호
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• pp.53-57
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• 2001

사출성형공정에서 미성형은 가장 빈번하게 발생하는 성형불량중의 하나이다. 이러한 미성형을 해결하기 위해 가상 경제적인 효율적인 방법은 공정조건을 개선하는 일이다. 그러나 대부분의 경우 사출 전문가의 오랜 기간 축적된 경험과 지식에 의존하기 때문에 여러 번의 시행착오을 겪어야 한다. 따라서 본 논문에서는 퍼지 알고리즘을 기반으로 하여 시스템에 적합한 공정조건을 찾는데 있어 시행착오를 줄이고, 또한 비전문가도 쉽게 적용학 수 있는 지능형 공정조건 생성 시스템을 제안하였다.

• 한국정밀공학회지
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• 제19권12호
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• pp.33-37
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• 2002

A short shot is a molded part that is incomplete because insufficient material was injected into the mold. Remedial actions to control the process conditions can be taken by the injection molding experts based on their knowledge and experience. However, it is very difficult for the non-experts to avoid short shot by finding the proper process conditions such as mold temperature, melt temperature and filling time. In this paper, an intelligent generator of the optimal process conditions based upon fuzzy logic algorithm is proposed so that trial and error can be minimized and the non-experts as well as the experts can also find the optimal process conditions.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.65-68
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• 2001

Short shot is a molded part that is incomplete since insufficient material was injected into the mold. Remedial actions to solve short shot can be done by injection molding experts based on their empirical knowledge. Modifying mold and part, changing resin to less viscous one, and adjusting process conditions are general remedies. Experts of injection molding might try to adjust process conditions such as mold temperature, melt temperature, injection time based on their empirical knowledge as the first remedy because adjustment of process conditions is the most economic way in time and cost. However it is difficult to find appropriate process conditions as they are highly coupled and there are so many elements to be considered. In this paper, a fuzzy logic algorithm has been proposed to find an appropriate mold temperature. With the percentage of the insufficient Quantity of an injection molded part, an appropriate mold temperature can be obtained by the fuzzy logic algorithm.

• 반도체디스플레이기술학회지
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• 제2권1호
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• pp.7-9
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• 2003

In order to predict the moldability of an injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network(FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the expert's conventional way which is similar to the golden section search algorithm.

• 한국반도체및디스플레이장비학회:학술대회논문집
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• 한국반도체및디스플레이장비학회 2002년도 추계학술대회 발표 논문집
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• pp.127-129
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• 2002

In order to predict the moldability of an injection molded part, a simulation of filling is needed. Short shot is one of the most frequent troubles encountered during injection molding process. The adjustment of process conditions is the most economic way to troubleshoot the problematic short shot in cost and time since the mold doesn't need to be modified at all. But it is difficult to adjust the process conditions appropriately in no times since it requires an empirical knowledge of injection molding. In this paper, the intelligent CAE system synergistically combines fuzzy-neural network(FNN) for heuristic knowledge with CAE programs for analytical knowledge. To evaluate the intelligent algorithms, a cellular phone flip has been chosen as a finite element model and filling analyses have been performed with a commercial CAE software. As the results, the intelligent CAE system drastically reduces the troubleshooting time of short shot in comparison with the expert's conventional way which is similar to the golden section search algorithm.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 춘계학술대회 논문집
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• pp.112-118
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• 2002

Injection molding process factors such as molding temperature, injection pressure, flow rate and flow velocity, must be controlled properly in filling and packing phases in the injection molding process. In this study, effects of these factors on the injection molding were investigated through the flow analysis fur the filling and packing phases. Molding troubles like flow mark, weld line, sink mark, short shot and warpage can be caused by these injection molding process factors. Among them, the short shot was caused by that the packing pressure could not reach properly to the filling end part in the packing phase and hence the flow rate could not be supplied to the full. In addition, as the flow rate for the volumetric shrinkage during the frozen phase could not be supplied properly by the packing pressure, the short shot appeared. Here, the volumetric shrinkage reduced with increasing the packing pressure and also the warpage of molded part increased with increasing the packing pressure.